This paper presents a technique for learning parameterized implied constraints. They can be added to a model to improve the solving process. Experiments on implied Gcc constraints ...
We study the problem of formally verifying shared memory multiprocessor executions against memory consistency models--an important step during post-silicon verification of multipro...
Memory models define an interface between programs written in some language and their implementation, determining which behaviour the memory (and thus a program) is allowed to hav...
Approximate linear programming (ALP) is an efficient approach to solving large factored Markov decision processes (MDPs). The main idea of the method is to approximate the optimal...
Abstract. Constraint logic programming combines declarativity and efficiency thanks to constraint solvers implemented for specific domains. Value withdrawal explanations have been ...